Overview

Dataset statistics

Number of variables10
Number of observations385500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

area[4] is highly overall correlated with area[5] and 3 other fieldsHigh correlation
area[5] is highly overall correlated with area[4] and 3 other fieldsHigh correlation
negpmax[5] is highly overall correlated with area[4] and 4 other fieldsHigh correlation
negpmax[6] is highly overall correlated with negpmax[5] and 1 other fieldsHigh correlation
pmax[5] is highly overall correlated with area[4] and 3 other fieldsHigh correlation
pmax[6] is highly overall correlated with area[4] and 4 other fieldsHigh correlation
tmax[4] is highly overall correlated with tmax[5]High correlation
tmax[5] is highly overall correlated with tmax[4]High correlation
tmax[5] is highly skewed (γ1 = 20.24180824)Skewed
negpmax[6] is highly skewed (γ1 = -257.7164663)Skewed
rms[4] has unique valuesUnique
rms[5] has unique valuesUnique

Reproduction

Analysis started2024-01-24 23:03:56.357970
Analysis finished2024-01-24 23:04:15.032137
Duration18.67 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

area[4]
Real number (ℝ)

HIGH CORRELATION 

Distinct384188
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5213254
Minimum-0.49863586
Maximum104.96812
Zeros0
Zeros (%)0.0%
Negative21
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:04:15.104473image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-0.49863586
5-th percentile2.3216744
Q14.7031204
median7.5806259
Q312.014731
95-th percentile24.837384
Maximum104.96812
Range105.46676
Interquartile range (IQR)7.3116107

Descriptive statistics

Standard deviation6.9237611
Coefficient of variation (CV)0.72718459
Kurtosis3.2835869
Mean9.5213254
Median Absolute Deviation (MAD)3.3457297
Skewness1.6340496
Sum3670471
Variance47.938468
MonotonicityNot monotonic
2024-01-25T00:04:15.212264image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.865856934 3
 
< 0.1%
6.140594482 3
 
< 0.1%
13.62075195 3
 
< 0.1%
6.967285156 3
 
< 0.1%
2.972354736 3
 
< 0.1%
5.716989136 2
 
< 0.1%
5.650036621 2
 
< 0.1%
6.837038574 2
 
< 0.1%
5.567172241 2
 
< 0.1%
7.193720703 2
 
< 0.1%
Other values (384178) 385475
> 99.9%
ValueCountFrequency (%)
-0.4986358643 1
< 0.1%
-0.3931811523 1
< 0.1%
-0.3698272705 1
< 0.1%
-0.3513922119 1
< 0.1%
-0.3258288574 1
< 0.1%
-0.3119622803 1
< 0.1%
-0.2386529541 1
< 0.1%
-0.2331945801 1
< 0.1%
-0.2261914063 1
< 0.1%
-0.1992340088 1
< 0.1%
ValueCountFrequency (%)
104.968125 1
< 0.1%
95.66599304 1
< 0.1%
94.38547546 1
< 0.1%
93.46904297 1
< 0.1%
88.70911987 1
< 0.1%
85.09000854 1
< 0.1%
84.97251465 1
< 0.1%
83.10847473 1
< 0.1%
81.24226074 1
< 0.1%
78.20518127 1
< 0.1%

tmax[4]
Real number (ℝ)

HIGH CORRELATION 

Distinct76110
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.332988
Minimum0
Maximum204.6
Zeros110
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:15.315503image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42.4
Q171
median71.6
Q372.222858
95-th percentile155.77583
Maximum204.6
Range204.6
Interquartile range (IQR)1.2228577

Descriptive statistics

Standard deviation29.896806
Coefficient of variation (CV)0.38659836
Kurtosis6.1608042
Mean77.332988
Median Absolute Deviation (MAD)0.6
Skewness2.0573781
Sum29811867
Variance893.81902
MonotonicityNot monotonic
2024-01-25T00:04:15.417366image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.4 26411
 
6.9%
72.2 25639
 
6.7%
71.8 25370
 
6.6%
71 24939
 
6.5%
71.2 24521
 
6.4%
72 24488
 
6.4%
71.6 24067
 
6.2%
70.8 21902
 
5.7%
72.4 21080
 
5.5%
70.6 14535
 
3.8%
Other values (76100) 152548
39.6%
ValueCountFrequency (%)
0 110
< 0.1%
0.4 115
< 0.1%
0.6 115
< 0.1%
0.8 157
< 0.1%
1 211
0.1%
1.093800595 1
 
< 0.1%
1.2 200
0.1%
1.226980445 1
 
< 0.1%
1.250044753 1
 
< 0.1%
1.258808365 1
 
< 0.1%
ValueCountFrequency (%)
204.6 105
< 0.1%
204.4 73
< 0.1%
204.2 49
< 0.1%
204 38
 
< 0.1%
203.8 29
 
< 0.1%
203.6 38
 
< 0.1%
203.4 19
 
< 0.1%
203.3420444 1
 
< 0.1%
203.2 16
 
< 0.1%
203 21
 
< 0.1%

rms[4]
Real number (ℝ)

UNIQUE 

Distinct385500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3758948
Minimum0.31782641
Maximum6.0381889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:15.511774image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.31782641
5-th percentile0.84257184
Q11.1239851
median1.3501728
Q31.6013131
95-th percentile1.9932775
Maximum6.0381889
Range5.7203625
Interquartile range (IQR)0.47732796

Descriptive statistics

Standard deviation0.35268033
Coefficient of variation (CV)0.25632799
Kurtosis0.48547022
Mean1.3758948
Median Absolute Deviation (MAD)0.23771119
Skewness0.43974414
Sum530407.43
Variance0.12438342
MonotonicityNot monotonic
2024-01-25T00:04:15.608192image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9380417258 1
 
< 0.1%
1.113969165 1
 
< 0.1%
1.228078111 1
 
< 0.1%
1.186353413 1
 
< 0.1%
1.165861944 1
 
< 0.1%
1.134571923 1
 
< 0.1%
1.507827476 1
 
< 0.1%
0.5895961992 1
 
< 0.1%
0.7577275689 1
 
< 0.1%
0.5119305327 1
 
< 0.1%
Other values (385490) 385490
> 99.9%
ValueCountFrequency (%)
0.3178264149 1
< 0.1%
0.3186246125 1
< 0.1%
0.3341709868 1
< 0.1%
0.3352037778 1
< 0.1%
0.3440018291 1
< 0.1%
0.3666824768 1
< 0.1%
0.3693241868 1
< 0.1%
0.3735303967 1
< 0.1%
0.37514582 1
< 0.1%
0.376426023 1
< 0.1%
ValueCountFrequency (%)
6.038188912 1
< 0.1%
5.538071041 1
< 0.1%
5.343040695 1
< 0.1%
5.169566252 1
< 0.1%
4.971241399 1
< 0.1%
4.758075961 1
< 0.1%
4.618326118 1
< 0.1%
4.538777004 1
< 0.1%
4.484659624 1
< 0.1%
4.209553951 1
< 0.1%

pmax[5]
Real number (ℝ)

HIGH CORRELATION 

Distinct382523
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.333002
Minimum2.476239
Maximum138.38165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:15.884968image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum2.476239
5-th percentile9.6673466
Q115.94942
median28.257567
Q358.928515
95-th percentile94.187664
Maximum138.38165
Range135.90541
Interquartile range (IQR)42.979095

Descriptive statistics

Standard deviation27.899214
Coefficient of variation (CV)0.70930801
Kurtosis-0.28422633
Mean39.333002
Median Absolute Deviation (MAD)15.759369
Skewness0.85737044
Sum15162872
Variance778.36613
MonotonicityNot monotonic
2024-01-25T00:04:16.031002image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.79319153 3
 
< 0.1%
19.12569885 3
 
< 0.1%
15.4340332 3
 
< 0.1%
15.58636169 3
 
< 0.1%
17.84398499 3
 
< 0.1%
14.94655457 3
 
< 0.1%
26.58236389 3
 
< 0.1%
58.86537781 3
 
< 0.1%
25.05706177 3
 
< 0.1%
20.9493866 3
 
< 0.1%
Other values (382513) 385470
> 99.9%
ValueCountFrequency (%)
2.476239014 1
< 0.1%
2.674658203 1
< 0.1%
2.821447754 1
< 0.1%
2.877566528 1
< 0.1%
2.945761108 1
< 0.1%
3.028723476 1
< 0.1%
3.123937988 1
< 0.1%
3.159783936 1
< 0.1%
3.167764282 1
< 0.1%
3.191207886 1
< 0.1%
ValueCountFrequency (%)
138.3816498 1
< 0.1%
137.1030701 1
< 0.1%
134.635434 1
< 0.1%
134.3267761 1
< 0.1%
134.0977203 1
< 0.1%
133.4767731 1
< 0.1%
133.2856689 1
< 0.1%
133.262085 1
< 0.1%
133.1631989 1
< 0.1%
133.0972687 1
< 0.1%

negpmax[5]
Real number (ℝ)

HIGH CORRELATION 

Distinct378918
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-20.186649
Minimum-2135.1261
Maximum-1.2378404
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:04:16.135847image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-2135.1261
5-th percentile-54.901535
Q1-31.219964
median-12.875058
Q3-6.2096764
95-th percentile-4.2760361
Maximum-1.2378404
Range2133.8883
Interquartile range (IQR)25.010287

Descriptive statistics

Standard deviation17.294225
Coefficient of variation (CV)-0.85671597
Kurtosis596.96907
Mean-20.186649
Median Absolute Deviation (MAD)7.9257889
Skewness-6.0413516
Sum-7781953.3
Variance299.09021
MonotonicityNot monotonic
2024-01-25T00:04:16.232693image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.578659058 3
 
< 0.1%
-4.904840088 3
 
< 0.1%
-4.726004028 3
 
< 0.1%
-7.422598267 3
 
< 0.1%
-4.795687866 3
 
< 0.1%
-10.629599 3
 
< 0.1%
-6.475338745 3
 
< 0.1%
-5.322229004 3
 
< 0.1%
-4.495870972 3
 
< 0.1%
-4.911791992 3
 
< 0.1%
Other values (378908) 385470
> 99.9%
ValueCountFrequency (%)
-2135.126117 1
< 0.1%
-893.3818428 1
< 0.1%
-287.4092626 1
< 0.1%
-187.5628258 1
< 0.1%
-160.8517062 1
< 0.1%
-112.2792431 1
< 0.1%
-109.6958566 1
< 0.1%
-89.34477224 1
< 0.1%
-81.16648865 1
< 0.1%
-80.37880859 1
< 0.1%
ValueCountFrequency (%)
-1.237840431 1
< 0.1%
-1.408457819 1
< 0.1%
-1.646505674 1
< 0.1%
-1.657708859 1
< 0.1%
-1.668808361 1
< 0.1%
-1.75915084 1
< 0.1%
-1.794954434 1
< 0.1%
-1.812451172 1
< 0.1%
-1.822229004 1
< 0.1%
-1.852177291 1
< 0.1%

area[5]
Real number (ℝ)

HIGH CORRELATION 

Distinct384887
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.714331
Minimum-0.28694275
Maximum137.89748
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:04:16.327892image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-0.28694275
5-th percentile6.7125835
Q110.925126
median17.630692
Q330.914978
95-th percentile46.903253
Maximum137.89748
Range138.18442
Interquartile range (IQR)19.989852

Descriptive statistics

Standard deviation13.035837
Coefficient of variation (CV)0.60033338
Kurtosis-0.30928607
Mean21.714331
Median Absolute Deviation (MAD)8.3947174
Skewness0.77546684
Sum8370874.4
Variance169.93306
MonotonicityNot monotonic
2024-01-25T00:04:16.430811image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.69107666 3
 
< 0.1%
9.017041016 3
 
< 0.1%
8.571398926 2
 
< 0.1%
11.84531006 2
 
< 0.1%
19.60683594 2
 
< 0.1%
12.58525391 2
 
< 0.1%
10.11114502 2
 
< 0.1%
8.389014893 2
 
< 0.1%
13.44497803 2
 
< 0.1%
30.48134155 2
 
< 0.1%
Other values (384877) 385478
> 99.9%
ValueCountFrequency (%)
-0.286942749 1
< 0.1%
-0.2517144775 1
< 0.1%
0.1102587891 1
< 0.1%
0.6065087891 1
< 0.1%
0.7407745361 1
< 0.1%
0.8548950195 1
< 0.1%
0.8578369141 1
< 0.1%
0.956418457 1
< 0.1%
1.015155029 1
< 0.1%
1.080264282 1
< 0.1%
ValueCountFrequency (%)
137.8974792 1
< 0.1%
128.4922791 1
< 0.1%
125.3773535 1
< 0.1%
113.5456696 1
< 0.1%
97.21516235 1
< 0.1%
95.00197266 1
< 0.1%
93.73051025 1
< 0.1%
92.62693359 1
< 0.1%
91.79156738 1
< 0.1%
90.34977173 1
< 0.1%

tmax[5]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct26087
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.544003
Minimum0
Maximum204.6
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:16.536301image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.6
Q171
median71.4
Q372
95-th percentile72.4
Maximum204.6
Range204.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.0084321
Coefficient of variation (CV)0.056027507
Kurtosis609.69448
Mean71.544003
Median Absolute Deviation (MAD)0.40319612
Skewness20.241808
Sum27580213
Variance16.067528
MonotonicityNot monotonic
2024-01-25T00:04:16.634239image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.4 37547
9.7%
71.8 37340
9.7%
71 37162
9.6%
71.2 35448
9.2%
72 35115
9.1%
71.6 35080
9.1%
70.8 34911
9.1%
72.2 33598
8.7%
70.6 31270
8.1%
72.4 17776
 
4.6%
Other values (26077) 50253
13.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
0.4 1
 
< 0.1%
0.6 1
 
< 0.1%
0.8 4
< 0.1%
1.4 3
< 0.1%
1.6 1
 
< 0.1%
1.8 3
< 0.1%
2 2
< 0.1%
2.2 3
< 0.1%
2.567266181 1
 
< 0.1%
ValueCountFrequency (%)
204.6 5
< 0.1%
204.4 4
< 0.1%
203.8 1
 
< 0.1%
203 1
 
< 0.1%
202.0928707 1
 
< 0.1%
201.9583775 1
 
< 0.1%
201.8 1
 
< 0.1%
201.5664408 1
 
< 0.1%
201.2 1
 
< 0.1%
201 2
 
< 0.1%

rms[5]
Real number (ℝ)

UNIQUE 

Distinct385500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3637315
Minimum0.27068674
Maximum5.6697771
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:16.735181image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.27068674
5-th percentile0.82938072
Q11.1120651
median1.3389698
Q31.5881442
95-th percentile1.9834087
Maximum5.6697771
Range5.3990903
Interquartile range (IQR)0.47607911

Descriptive statistics

Standard deviation0.35243875
Coefficient of variation (CV)0.25843705
Kurtosis0.46176765
Mean1.3637315
Median Absolute Deviation (MAD)0.23715379
Skewness0.44068663
Sum525718.5
Variance0.12421307
MonotonicityNot monotonic
2024-01-25T00:04:16.831957image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.412877201 1
 
< 0.1%
1.025774287 1
 
< 0.1%
1.381680692 1
 
< 0.1%
1.233184478 1
 
< 0.1%
1.037192862 1
 
< 0.1%
1.510124974 1
 
< 0.1%
0.900202838 1
 
< 0.1%
1.620824648 1
 
< 0.1%
1.29273163 1
 
< 0.1%
0.9674871029 1
 
< 0.1%
Other values (385490) 385490
> 99.9%
ValueCountFrequency (%)
0.2706867438 1
< 0.1%
0.294354428 1
< 0.1%
0.3355097512 1
< 0.1%
0.3595357764 1
< 0.1%
0.3607931844 1
< 0.1%
0.3616352483 1
< 0.1%
0.3660771654 1
< 0.1%
0.3684391798 1
< 0.1%
0.3703964835 1
< 0.1%
0.3725735878 1
< 0.1%
ValueCountFrequency (%)
5.669777061 1
< 0.1%
5.52557677 1
< 0.1%
5.394941245 1
< 0.1%
5.150317714 1
< 0.1%
4.910367448 1
< 0.1%
4.843243003 1
< 0.1%
4.722864972 1
< 0.1%
4.637080037 1
< 0.1%
4.171324506 1
< 0.1%
4.14364169 1
< 0.1%

pmax[6]
Real number (ℝ)

HIGH CORRELATION 

Distinct377303
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.907669
Minimum1.8830017
Maximum128.19901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:16.928439image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.8830017
5-th percentile4.0616402
Q15.4025037
median8.6747253
Q316.1976
95-th percentile53.719611
Maximum128.19901
Range126.31601
Interquartile range (IQR)10.795096

Descriptive statistics

Standard deviation16.613431
Coefficient of variation (CV)1.1144218
Kurtosis8.0653096
Mean14.907669
Median Absolute Deviation (MAD)3.8891342
Skewness2.7220708
Sum5746906.2
Variance276.0061
MonotonicityNot monotonic
2024-01-25T00:04:17.035128image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.736099243 4
 
< 0.1%
5.210751343 4
 
< 0.1%
4.372338867 4
 
< 0.1%
4.909204102 4
 
< 0.1%
5.084622192 4
 
< 0.1%
4.909317017 4
 
< 0.1%
5.625576782 4
 
< 0.1%
5.24274292 3
 
< 0.1%
5.165380859 3
 
< 0.1%
6.443426514 3
 
< 0.1%
Other values (377293) 385463
> 99.9%
ValueCountFrequency (%)
1.883001709 1
< 0.1%
1.941110229 1
< 0.1%
2.028720093 1
< 0.1%
2.035980225 1
< 0.1%
2.091317749 1
< 0.1%
2.122937012 1
< 0.1%
2.143798828 1
< 0.1%
2.144796753 1
< 0.1%
2.155578613 1
< 0.1%
2.156524658 1
< 0.1%
ValueCountFrequency (%)
128.1990082 1
< 0.1%
124.0306061 1
< 0.1%
123.7841431 1
< 0.1%
122.9109039 1
< 0.1%
121.1634338 1
< 0.1%
121.1417328 1
< 0.1%
121.1042511 1
< 0.1%
121.0805603 1
< 0.1%
120.7872864 1
< 0.1%
120.5332977 1
< 0.1%

negpmax[6]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct362020
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.8140836
Minimum-10967.68
Maximum-0.87525903
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:04:17.137177image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-10967.68
5-th percentile-30.692666
Q1-6.9770561
median-5.2448395
Q3-4.4694611
95-th percentile-3.6167439
Maximum-0.87525903
Range10966.805
Interquartile range (IQR)2.5075951

Descriptive statistics

Standard deviation26.239272
Coefficient of variation (CV)-2.9769711
Kurtosis91489.418
Mean-8.8140836
Median Absolute Deviation (MAD)0.96929145
Skewness-257.71647
Sum-3397829.2
Variance688.4994
MonotonicityNot monotonic
2024-01-25T00:04:17.238652image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.206686401 5
 
< 0.1%
-4.986428833 5
 
< 0.1%
-5.164105225 5
 
< 0.1%
-5.486227417 5
 
< 0.1%
-4.819003296 5
 
< 0.1%
-4.945831299 4
 
< 0.1%
-5.236251831 4
 
< 0.1%
-4.290420532 4
 
< 0.1%
-4.522979736 4
 
< 0.1%
-5.46026001 4
 
< 0.1%
Other values (362010) 385455
> 99.9%
ValueCountFrequency (%)
-10967.68044 1
< 0.1%
-5631.924716 1
< 0.1%
-5238.83206 1
< 0.1%
-4084.062022 1
< 0.1%
-3720.689005 1
< 0.1%
-2563.578544 1
< 0.1%
-2178.87929 1
< 0.1%
-1927.087384 1
< 0.1%
-1049.149259 1
< 0.1%
-1034.959101 1
< 0.1%
ValueCountFrequency (%)
-0.8752590319 1
< 0.1%
-0.9923668284 1
< 0.1%
-1.36513904 1
< 0.1%
-1.369527521 1
< 0.1%
-1.414624211 1
< 0.1%
-1.470422455 1
< 0.1%
-1.572550191 1
< 0.1%
-1.58181484 1
< 0.1%
-1.590478515 1
< 0.1%
-1.639253348 1
< 0.1%

Interactions

2024-01-25T00:04:13.263052image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.078322image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.167520image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.237466image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.317900image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.505874image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.582238image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.751831image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.881781image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.118833image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.377756image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.187978image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.268218image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.346487image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.424826image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.608380image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.694395image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.862137image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.996170image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.230814image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.480677image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.292290image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.370213image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.450123image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.530755image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.714001image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.813623image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.974985image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.105899image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.342939image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.586474image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.400022image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.476534image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.554735image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.639971image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.819693image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.937615image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.084392image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.217880image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.458661image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.698003image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.508208image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.583786image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.668145image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.755890image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.928087image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.058046image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.200123image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.336532image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.575114image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.804144image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.613082image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.691081image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
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2024-01-25T00:04:08.031828image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.168335image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.308143image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.446940image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.688378image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.914221image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.724467image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.805172image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.887491image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.069868image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.146436image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.288154image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.421969image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.559758image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.812000image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:14.018152image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.830363image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.906087image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.990156image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.175260image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.250252image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.402330image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.529685image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.671934image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:12.924572image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:14.119884image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:03.948018image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.009121image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.098755image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.282666image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.358554image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.518276image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.640411image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.781873image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.037895image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:14.223589image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:04.059686image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:05.116219image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:06.209426image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:07.392064image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:08.471681image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:09.631911image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:10.751374image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:11.898458image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:13.152993image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-01-25T00:04:17.312042image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
area[4]area[5]negpmax[5]negpmax[6]pmax[5]pmax[6]rms[4]rms[5]tmax[4]tmax[5]
area[4]1.0000.640-0.629-0.4170.6540.620-0.0030.001-0.146-0.113
area[5]0.6401.000-0.910-0.4910.9710.8180.0010.001-0.143-0.184
negpmax[5]-0.629-0.9101.0000.528-0.948-0.8230.000-0.0020.1510.193
negpmax[6]-0.417-0.4910.5281.000-0.499-0.532-0.002-0.0010.1050.103
pmax[5]0.6540.971-0.948-0.4991.0000.8380.0010.002-0.151-0.195
pmax[6]0.6200.818-0.823-0.5320.8381.0000.0000.000-0.135-0.160
rms[4]-0.0030.0010.000-0.0020.0010.0001.0000.008-0.014-0.002
rms[5]0.0010.001-0.002-0.0010.0020.0000.0081.000-0.004-0.005
tmax[4]-0.146-0.1430.1510.105-0.151-0.135-0.014-0.0041.0000.616
tmax[5]-0.113-0.1840.1930.103-0.195-0.160-0.002-0.0050.6161.000

Missing values

2024-01-25T00:04:14.325188image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-25T00:04:14.541029image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

area[4]tmax[4]rms[4]pmax[5]negpmax[5]area[5]tmax[5]rms[5]pmax[6]negpmax[6]
07.21525970.5941600.9380429.322305-19.4771015.52079172.4000001.4128773.077338-19.239130
16.666403156.5985351.1097689.373914-3.8967776.82166771.0000001.4890115.424356-4.675986
21.39749371.8000001.1214837.499896-5.3434277.26022271.8000001.5479365.846233-5.021164
35.184150197.7259321.84909910.422260-4.9167915.48052772.4000000.8095505.157927-3.594675
41.4235942.6000001.47489612.557806-4.5826299.22284771.1602011.8145206.115046-4.172168
51.48227515.8000001.2967508.969864-4.7535685.28102471.2000001.1242395.716074-4.395551
67.000577200.7619221.88454512.389180-5.5624858.49864571.9026440.8217876.625668-3.567569
72.28297523.2000000.83293210.170212-3.75636310.88070772.2000001.2054915.895798-4.476944
81.868380186.0000001.2081226.997684-5.6274993.81986571.8000002.1870773.784637-6.237152
914.53300570.8551272.04928810.014044-5.7485906.46477871.0000002.0619635.442926-4.246588
area[4]tmax[4]rms[4]pmax[5]negpmax[5]area[5]tmax[5]rms[5]pmax[6]negpmax[6]
3854909.02206472.2943371.3800599.342075-5.3921616.35010972.4000001.1188467.540115-4.589096
3854918.84614371.8000001.16269813.108267-5.2414037.41186671.8000001.0492665.133954-4.728412
3854928.99731071.4000001.36576415.378343-4.6664899.92381371.3521940.9932317.581711-4.874847
3854937.17616071.2000001.33988412.879260-6.6870859.57864571.2000001.4114485.393158-6.087905
3854948.04907872.2000002.0519959.427908-5.0327246.00453072.4000001.1258914.279150-4.681360
3854957.32917171.2000001.49886912.878128-5.1620947.17511671.2000001.2963574.604367-4.497623
3854968.17785971.4610991.4900029.729486-5.5820985.11137071.6000001.5630364.075574-4.323596
3854978.72131271.4000001.18660813.104062-4.6336707.31089771.4000001.1257816.381778-5.319577
3854985.56993171.4000001.63609411.139015-4.63046415.77706971.3644221.57635614.606870-4.281985
3854999.24036871.8000000.98045913.715833-18.86324810.31719071.8000001.5423164.348273-21.837317